Publisert: 24.11.21

PhD position – Decision Analytics for Hydropower Reservoir Management

This is a 3-year PhD position with the possibility of an additional year with working duties at the Department of Industrial Economics and Technology Management – Section Managerial Economics, Finance and Operation Research. The position is resident at NTNUs campus in Trondheim. It is an educational position, which will provide promising research talents the opportunity for professional development towards a PhD-degree. The position is connected to the PhD program at the Faculty of Economics and Management and the faculty will be your employer.

The position is part of the SusHydro project at NTNU that seeks to find innovative and cross-sectoral solutions that shed light on a wider range of services that hydropower and water reservoirs can contribute and shed light on how synergies and conflicts between different sustainability goals can be identified and balanced. SusHydro will do this by putting together a team of experienced professionals and talented young researchers with a background in hydrology and water resource analysis, life cycle assessment, modeling of the energy system, economics, biology and social sciences. Solutions will be developed through case studies in Norway and areas of Africa with rich hydropower resources.

About the position

This position is within operations research. The SusHydro project will develop models and methods for coordinated hydropower reservoir operations, when several owners make possibly independent operational decisions. Operations are subject to uncertainty in electricity market prices and runoff/inflow, for which different owners may have distinct expectations. We will study how jointly owned reservoirs are operated in practice and which characteristics of organizational structures and contracts that govern joint operations. We will analyze how the interests of the owners are and should be balanced with sustainability issues and interests of other stakeholders. We intend to chart best practices, analyze operational properties of these, and develop analytical models to support improved performance regarding relevant sustainability goals including considerations of efficiency, climate change and economic value of flexibility. In addition to new models, this requires advanced stochastic optimization techniques and data driven optimization. Machine learning and simulation techniques will play an important role in the project.

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Department of Industrial Economics and Technology Management

IØT has challenging and inspiring educational programmes and research projects in the cross-disciplinary field of technology management. Through its programmes of study, IØT educates candidates with a solid technological basis in methodology and theory on how to develop and manage technologically based organisations.


Participation in, and development of, research projects in close co-operation with Norwegian industry, the department is also developing models, tools and methods for how to manage Norwegian industry.

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